PDF (Portable Document Format) is recognized as an industry standard and is among the most prevalent formats for the presentation and exchange of information. In the realms of supply chain management, business administration, and procurement, several types of business documents are commonly shared in PDF format, including:

• Invoices
• Contracts
• Purchase orders
• Reports
• Human resources forms
• Shipping notes
• Presentations
• Product and price lists

Although PDFs are effective for information exchange, the process of extracting insights from the data contained within these files can be both challenging and labour-intensive due to the unstructured nature of the information, which may include text and images.

The task of manually extracting unstructured data from each PDF file further complicates the process. This is where PDF scraping proves beneficial, as it facilitates the automated extraction of data from PDF files.

Manual PDF Data Extraction:

It takes a lot of resources to manually extract data from PDFs. A team member must choose the table and manually copy all of the data in the PDF tables, which might result in mistakes and lengthy turnaround times.

Hundreds of PDF documents in the process make it much more challenging. Even with numerous resources available for data retrieval, human data entry might take days or weeks to produce usable information if data extraction is not automated.

Manual Data Extraction: Analysing Cost and Efficiency

To provide clarity on the financial implications of extracting information from PDFs, let us consider some figures. Suppose you employ an analyst whose primary responsibility is to extract and analyse data from unstructured PDF documents. The associated costs may be outlined as follows:

• The average annual salary for an analyst is approximately £60,000 (based on the US median wage).
• An analyst typically dedicates around 70% of their daily work hours to data extraction, which encompasses the processes of extraction, cleaning, and preparation.
• Consequently, the total cost attributed to an analyst for extracting and preparing unstructured data from PDFs amounts to £42,000.

In this manual data extraction scenario, a significant portion of the analyst’s time and effort is consumed by data preparation rather than actual analysis, leading to potential inaccuracies.

Automated PDF Data Extraction:

In light of the challenges posed by manual data extraction, an effective solution for businesses is to leverage third-party tools that enable the parsing of diverse PDF documents with minimal human oversight. Below are the ways in which PDF data extraction software can assist your enterprise:

• You can design and implement rules and formulas to facilitate the automatic transfer of data from PDF files to Excel. This approach significantly reduces the time spent on manual searches and the copying or rekeying of essential information.
• The software allows for the conversion of data from images into text using built-in OCR technology, thereby eliminating the need for manual data entry. This process reduces the risk of typographical errors and other mistakes during extraction.
• Artificial intelligence can be utilized to streamline the data extraction process from PDFs. AI technology can identify critical fields and extract them automatically.
• You can automate the complete extraction process and execute it on a batch of PDF documents, enabling the collection of all necessary information in a single operation. This boosts business efficiency and guarantees that data is available as required.

How Can PF Data Extraction Be Automated?

One of these two approaches can be used to automate the capture of PDF data. The first approach is more resource-intensive, time-consuming, and more likely to involve trial and error. On the other hand, a data extraction tool makes the second option fully automated.

1. Make use of codes and scripts:

Creating document processing programs or scripts to extract the required data from PDF documents is the first approach. For the majority of firms, this is not advised due to the high level of complexity and the need for specialized developer resources. Code frequently needs to be rewritten or modified if the document structure changes.

2. Employ a Data Extraction Tool:

To extract data from PDFs, use a program like Report Miner. It is an automation solution for data extraction that has auto data extraction built in. It offers an easy-to-use interface that doesn’t require coding. Therefore, this is advised for companies that need to reliably and swiftly extract information from large amounts of PDFs.